Data Quality

Data Integrity vs. Data Quality: Are they the same?

Data integrity is a broad discipline that governs the entire data lifecycle - from how it is collected, to how it is stored, accessed, and used.

Data integrity is maintained by a set of processes, rules, and standards with the objective to preserve the overall accuracy and data security in regard to regulatory compliance frameworks —such as the General Data Protection Regulation (GDPR) or the (CCPA) and ensure that data remains accurate, consistent, and unaltered.

However, despite its similiarities, data integrity should not be confused with data quality.

Of course, data quality is a crucial part of data integrity. Yet, data integrity encompasses every aspect of data quality and goes further by implementing a set of rules and processes that govern how data is entered, stored, and transferred.

In this sense, while data quality is a good starting point and both data quality and data integrity are crucial when taking data-driven decisions, data integrity elevates data’s level of usefulness to an organization and ultimately drives better business decisions by encompassing its whole life cycle.

Learn more about it in the following blog post.

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